Arrival of Big Data Opens Up a New Range of Analytics

With Strata, IBM IOD, and Teradata Partners conferences all occurring this week, it’s not surprising that this is a big week for Hadoop-related announcements. The common thread of announcements is essentially, “We know that Hadoop is not known for performance, but we’re getting better at it, and we’re going to make it look more like SQL.” In essence, Hadoop and SQL worlds are converging, and you’re going to be able to perform interactive BI analytics on it.

The opportunity and challenge of Big Data from new platforms such as Hadoop is that it opens a new range of analytics. On one hand, Big Data analytics have updated and revived programmatic access to data, which happened to be the norm prior to the advent of SQL. There are plenty of scenarios where taking programmatic approaches are far more efficient, such as dealing with time series data or graph analysis to map many-to-many relationships.

It also leverages in-memory data grids such as Oracle Coherence, IBM WebSphere eXtreme Scale, GigaSpaces and others, and, where programmatic development (usually in Java) proved more efficient for accessing highly changeable data for web applications where traditional paths to the database would have been I/O-constrained. Conversely Advanced SQL platforms such as Greenplum and Teradata Aster have provided support for MapReduce-like programming because, even with structured data, sometimes using a Java programmatic framework is a more efficient way to rapidly slice through volumes of data.

But when you talk analytics, you can’t simply write off the legions of SQL developers that populate enterprise IT shops.

Until now, Hadoop has not until now been for the SQL-minded. The initial path was, find someone to do data exploration inside Hadoop, but once you’re ready to do repeatable analysis, ETL (or ELT) it into a SQL data warehouse. That’s been the pattern with Oracle Big Data Appliance (use Oracle loader and data integration tools), and most Advanced SQL platforms; most data integration tools provide Hadoop connectors that spawn their own MapReduce programs to ferry data out of Hadoop. Some integration tool providers, like Informatica, offer tools to automate parsing of Hadoop data. Teradata Aster and Hortonworks have been talking up the potentials of HCatalog, in actuality an enhanced version of Hive with RESTful interfaces, cost optimizers, and so on, to provide a more SQL friendly view of data residing inside Hadoop.

But when you talk analytics, you can’t simply write off the legions of SQL developers that populate enterprise IT shops. And beneath the veneer of chaos, there is an implicit order to most so-called “unstructured” data that is within the reach programmatic transformation approaches that in the long run could likely be automated or packaged inside a tool.

At Ovum, we have long believed that for Big Data to crossover to the mainstream enterprise, that it must become a first-class citizen with IT and the data center. The early pattern of skunk works projects, led by elite, highly specialized teams of software engineers from Internet firms to solve Internet-style problems (e.g., ad placement, search optimization, customer online experience, etc.) are not the problems of mainstream enterprises. And neither is the model of recruiting high-priced talent to work exclusively on Hadoop sustainable for most organizations; such staffing models are not sustainable for mainstream enterprises. It means that Big Data must be consumable by the mainstream of SQL developers.

Making Hadoop more SQL-like is hardly new

Hive and Pig became Apache Hadoop projects because of the need for SQL-like metadata management and data transformation languages, respectively; HBase emerged because of the need for a table store to provide a more interactive face – although as a very sparse, rudimentary column store, does not provide the efficiency of an optimized SQL database (or the extreme performance of some columnar variants). Sqoop in turn provides a way to pipeline SQL data into Hadoop, a use case that will grow more common as organizations look to Hadoop to provide scalable and cheaper storage than commercial SQL. While these Hadoop subprojects that did not exactly make Hadoop look like SQL, they provided building blocks from which many of this week’s announcements leverage.

Progress marches on

One train of thought is that if Hadoop can look more like a SQL database, more operations could be performed inside Hadoop. That’s the theme behind Informatica’s long-awaited enhancement of its PowerCenter transformation tool to work natively inside Hadoop. Until now, PowerCenter could extract data from Hadoop, but the extracts would have to be moved to a staging server where the transformation would be performed for loading to the familiar SQL data warehouse target. The new offering, PowerCenter Big Data Edition, now supports an ELT pattern that uses the power of MapReduce processes inside Hadoop to perform transformations. The significance is that PowerCenter users now have a choice: load the transformed data to HBase, or continue loading to SQL.

There is growing support for packaging Hadoop inside a common hardware appliance with Advanced SQL. EMC Greenplum was the first out of gate with DCA (Data Computing Appliance) that bundles its own distribution of Apache Hadoop (not to be confused with Greenplum MR, a software only product that is accompanied by a MapR Hadoop distro).

Teradata Aster has just joined the fray with Big Analytics Appliance, bundling the Hortonworks Data Platform Hadoop; this move was hardly surprising given their growing partnership around HCatalog, an enhancement of the SQL-like Hive metadata layer of Hadoop that adds features such as a cost optimizer and RESTful interfaces that make the metadata accessible without the need to learn MapReduce or Java. With HCatalog, data inside Hadoop looks like another Aster data table.

Not coincidentally, there is a growing array of analytic tools that are designed to execute natively inside Hadoop. For now they are from emerging players like Datameer (providing a spreadsheet-like metaphor; which just announced an app store-like marketplace for developers), Karmasphere (providing an application develop tool for Hadoop analytic apps), or a more recent entry, Platfora (which caches subsets of Hadoop data in memory with an optimized, high performance fractal index).

CIO, CTO & Developer Resources

Yet, even with Hadoop analytic tooling, there will still be a desire to disguise Hadoop as a SQL data store, and not just for data mapping purposes.

Yet, even with Hadoop analytic tooling, there will still be a desire to disguise Hadoop as a SQL data store, and not just for data mapping purposes. Hadapt has been promoting a variant where it squeezes SQL tables inside HDFS file structures – not exactly a no-brainer as it must shoehorn tables into a file system with arbitrary data block sizes. Hadapt’s approach sounds like the converse of object-relational stores, but in this case, it is dealing with a physical rather than a logical impedance mismatch.

Hadapt promotes the ability to query Hadoop directly using SQL. Now, so does Cloudera. It has just announced Impala, a SQL-based alternative to MapReduce for querying the SQL-like Hive metadata store, supporting most but not all forms of SQL processing (based on SQL 92; Impala lacks triggers, which Cloudera deems low priority). Both Impala and MapReduce rely on parallel processing, but that’s where the similarity ends. MapReduce is a blunt instrument, requiring Java or other programming languages; it splits a job into multiple, concurrently, pipelined tasks where, at each step along the way, reads data, processes it, and writes it back to disk and then passes it to the next task.

Conversely, Impala takes a shared nothing, MPP approach to processing SQL jobs against Hive; using HDFS, Cloudera claims roughly 4x performance against MapReduce; if the data is in HBase, Cloudera claims performance multiples up to a factor of 30. For now, Impala only supports row-based views, but with columnar (on Cloudera’s roadmap), performance could double. Cloudera plans to release a real-time query (RTQ) offering that, in effect, is a commercially supported version of Impala.

By contrast, Teradata Aster and Hortonworks promote a SQL MapReduce approach that leverages HCatalog, an incubating Apache project that is a superset of Hive that Cloudera does not currently include in its roadmap. For now, Cloudera claims bragging rights for performance with Impala; over time, Teradata Aster will promote the manageability of its single appliance, and with the appliance has the opportunity to counter with hardware optimization.

The road to SQL/programmatic convergence

Either way – and this is of interest only to purists – any SQL extension to Hadoop will be outside the Hadoop project. But again, that’s an argument for purists. What’s more important to enterprises is getting the right tool for the job – whether it is the flexibility of SQL or raw power of programmatic approaches.

SQL convergence is the next major battleground for Hadoop. Cloudera is for now shunning HCatalog, an approach backed by Hortonworks and partner Teradata Aster. The open question is whether Hortonworks can instigate a stampede of third parties to overcome Cloudera’s resistance. It appears that beyond Hive, the SQL face of Hadoop will become a vendor-differentiated layer.

Part of conversion will involve a mix of cross-training and tooling automation. Savvy SQL developers will cross train to pick up some of the Java- or Java-like programmatic frameworks that will be emerging. Tooling will help lower the bar, reducing the degree of specialized skills necessary.

And for programming frameworks, in the long run, MapReduce won’t be the only game in town. It will always be useful for large-scale jobs requiring brute force, parallel, sequential processing. But the emerging YARN framework, which deconstructs MapReduce to generalize the resource management function, will provide the management umbrella for ensuring that different frameworks don’t crash into one another by trying to grab the same resources. But YARN is not yet ready for primetime – for now it only supports the batch job pattern of MapReduce. And that means that YARN is not yet ready for Impala or vice versa.

Either way – and this is of interest only to purists – any SQL extension to Hadoop will be outside the Hadoop project. But again, that’s an argument for purists.

Of course, mainstreaming Hadoop – and Big Data platforms in general – is more than just a matter of making it all look like SQL. Big Data platforms must be manageable and operable by the people who are already in IT; they will need some new skills and grow accustomed to some new practices (like exploratory analytics), but the new platforms must also look and act familiar enough. Not all announcements this week were about SQL; for instance, MapR is throwing a gauntlet to the Apache usual suspects by extending its management umbrella beyond the proprietary NFS-compatible file system that is its core IP to the MapReduce framework and HBase, making a similar promise of high performance.

On the horizon, EMC Isilon and NetApp are proposing alternatives promising a more efficient file system but at the “cost” of separating the storage from the analytic processing. And at some point, the Hadoop vendor community will have to come to grips with capacity utilization issues, because in the mainstream enterprise world, no CFO will approve the purchase of large clusters or grids that get only 10 – 15 percent utilization. Keep an eye on VMware’s Project Serengeti.

They must be good citizens in data centers that need to maximize resource (e.g., virtualization, optimized storage); must comply with existing data stewardship policies and practices; and must fully support existing enterprise data and platform security practices. These are all topics for another day.

Tony Baer is Principal Analyst with Ovum, leading Ovum’s research on the software lifecycle. Working in concert with other members of Ovum’s software group, his research covers the full lifecycle from design and development to deployment and management. Areas of focus include application lifecycle management, software development methodologies (including agile), SOA, IT service management/ITIL, and IT management/governance.

Baer has been a noted authority on software development platforms and integration architecture for nearly 20 years. Prior to joining Ovum, he was an independent analyst whose company ‘onStrategies’ delivered software development and integration tools to vendors with technology assessment and market positioning services. He also led Computerwire’s CIO Agenda and Computer Finance end-user best practices research services.

The Software Defined Data Center (SDDC), which enables organizations to seamlessly run in a hybrid cloud model (public + private cloud), is here to stay. IDC estimates that the software-defined networking market will be valued at $3.7 billion by 2016.
Security is a key component and benefit of the SDDC, and offers an opportunity to build security 'from the ground up' and weave it into the environment from day one.
In his session at 16th Cloud Expo, Reuven Harrison, CTO and Co-Founder of Tufin,...

JavaScript is primarily a client-based dynamic scripting language most commonly used within web browsers as client-side scripts to interact with the user, browser, and communicate asynchronously to servers.
If you have been part of any web-based development, odds are you have worked with JavaScript in one form or another. In this article, I'll focus on the aspects of JavaScript that are relevant within the Node.js environment.

Alibaba, the world’s largest ecommerce provider, has pumped over a $1 billion into its subsidiary, Aliya, a cloud services provider. This is perhaps one of the biggest moments in the global Cloud Wars that signals the entry of China into the main arena. Here is why this matters.
The cloud industry worldwide is being propelled into fast growth by tremendous demand for cloud computing services. Cloud, which is highly scalable and offers low investment and high computational capabilities to end us...

One of the ways to increase scalability of services – and applications – is to go “stateless.” The reasons for this are many, but in general by eliminating the mapping between a single client and a single app or service instance you eliminate the need for resources to manage state in the app (overhead) and improve the distributability (I can make up words if I want) of requests across a pool of instances. The latter occurs because sessions don’t need to hang out and consume resources that could ...

Approved this February by the Internet Engineering Task Force (IETF), HTTP/2 is the first major update to HTTP since 1999, when HTTP/1.1 was standardized. Designed with performance in mind, one of the biggest goals of HTTP/2 implementation is to decrease latency while maintaining a high-level compatibility with HTTP/1.1. Though not all testing activities will be impacted by the new protocol, it's important for testers to be aware of any changes moving forward.

"We've just seen a huge influx of new partners coming into our ecosystem, and partners building unique offerings on top of our API set," explained Seth Bostock, Chief Executive Officer at IndependenceIT, in this SYS-CON.tv interview at 16th Cloud Expo, held June 9-11, 2015, at the Javits Center in New York City.

This week, I joined SOASTA as Senior Vice President of Performance Analytics. Given my background in cloud computing and distributed systems operations — you may have read my blogs on CNET or GigaOm — this may surprise you, but I want to explain why this is the perfect time to take on this opportunity with this team. In fact, that’s probably the best way to break this down. To explain why I’d leave the world of infrastructure and code for the world of data and analytics, let’s explore the timing...

SYS-CON Events announced today that HPM Networks will exhibit at the 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA.
For 20 years, HPM Networks has been integrating technology solutions that solve complex business challenges. HPM Networks has designed solutions for both SMB and enterprise customers throughout the San Francisco Bay Area.

You often hear the two titles of "DevOps" and "Immutable Infrastructure" used independently.
In his session at DevOps Summit, John Willis, Technical Evangelist for Docker, covered the union between the two topics and why this is important. He provided an overview of Immutable Infrastructure then showed how an Immutable Continuous Delivery pipeline can be applied as a best practice for "DevOps." He ended the session with some interesting case study examples.

Learn how to solve the problem of keeping files in sync between multiple Docker containers.
In his session at 16th Cloud Expo, Aaron Brongersma, Senior Infrastructure Engineer at Modulus, discussed using rsync, GlusterFS, EBS and Bit Torrent Sync. He broke down the tools that are needed to help create a seamless user experience.
In the end, can we have an environment where we can easily move Docker containers, servers, and volumes without impacting our applications? He shared his results so yo...

Auto-scaling environments, micro-service architectures and globally-distributed teams are just three common examples of why organizations today need automation and interoperability more than ever. But is interoperability something we simply start doing, or does it require a reexamination of our processes? And can we really improve our processes without first making interoperability a requirement for how we choose our tools?

Cloud Migration Management (CMM) refers to the best practices for planning and managing migration of IT systems from a legacy platform to a Cloud Provider through a combination professional services consulting and software tools.
A Cloud migration project can be a relatively simple exercise, where applications are migrated ‘as is’, to gain benefits such as elastic capacity and utility pricing, but without making any changes to the application architecture, software development methods or busine...

The Internet of Things. Cloud. Big Data. Real-Time Analytics. To those who do not quite understand what these phrases mean (and let’s be honest, that’s likely to be a large portion of the world), words like “IoT” and “Big Data” are just buzzwords. The truth is, the Internet of Things encompasses much more than jargon and predictions of connected devices. According to Parker Trewin, Senior Director of Content and Communications of Aria Systems, “IoT is big news because it ups the ante: Reach out ...

At DevOps Summit NY there’s been a whole lot of talk about not just DevOps, but containers, IoT, and microservices. Sessions focused not just on the cultural shift needed to grow at scale with a DevOps approach, but also made sure to include the network ”plumbing” needed to ensure success as applications decompose into the microservice architectures enabling rapid growth and support for the Internet of (Every)Things.

Our guest on the podcast this week is Adrian Cockcroft, Technology Fellow at Battery Ventures. We discuss what makes Docker and Netflix highly successful, especially through their use of well-designed IT architecture and DevOps.

Explosive growth in connected devices. Enormous amounts of data for collection and analysis. Critical use of data for split-second decision making and actionable information. All three are factors in making the Internet of Things a reality. Yet, any one factor would have an IT organization pondering its infrastructure strategy.
How should your organization enhance its IT framework to enable an Internet of Things implementation? In his session at @ThingsExpo, James Kirkland, Red Hat's Chief Arch...

Digital Transformation is the ultimate goal of cloud computing and related initiatives. The phrase is certainly not a precise one, and as subject to hand-waving and distortion as any high-falutin' terminology in the world of information technology.
Yet it is an excellent choice of words to describe what enterprise IT—and by extension, organizations in general—should be working to achieve.
Digital Transformation means:
handling all the data types being found and created in the organizat...

Public Cloud IaaS started its life in the developer and startup communities and has grown rapidly to a $20B+ industry, but it still pales in comparison to how much is spent worldwide on IT: $3.6 trillion. In fact, there are 8.6 million data centers worldwide, the reality is many small and medium sized business have server closets and colocation footprints filled with servers and storage gear. While on-premise environment virtualization may have peaked at 75%, the Public Cloud has lagged in adop...

MuleSoft has announced the findings of its 2015 Connectivity Benchmark Report on the adoption and business impact of APIs.
The findings suggest traditional businesses are quickly evolving into "composable enterprises" built out of hundreds of connected software services, applications and devices. Most are embracing the Internet of Things (IoT) and microservices technologies like Docker. A majority are integrating wearables, like smart watches, and more than half plan to generate revenue with ...

Rapid innovation, changing business landscapes, and new IT demands force businesses to make changes quickly. The DevOps approach is a way to increase business agility through collaboration, communication, and integration across different teams in the IT organization.
In his session at DevOps Summit, Chris Van Tuin, Chief Technologist for the Western US at Red Hat, will discuss:
The acceleration of application delivery for the business with DevOps

JavaScript is primarily a client-based dynamic scripting language most commonly used within web browsers as client-side scripts to interact with the user, browser, and communicate asynchronously to servers.
If you have been part of any web-based development, odds are you have worked with JavaScript in one form or another. In this article, I'll focus on the aspects of JavaScript that are relevant within the Node.js environment.

Alibaba, the world’s largest ecommerce provider, has pumped over a $1 billion into its subsidiary, Aliya, a cloud services provider. This is perhaps one of the biggest moments in the global Cloud Wars that signals the entry of China into the main arena. Here is why this matters.
The cloud industry worldwide is being propelled into fast growth by tremendous demand for cloud computing services. Cloud, which is highly scalable and offers low investment and high computational capabilities to end users by eliminating the need to buy costly infrastructure and instead rent it from cloud providers, i...

One of the ways to increase scalability of services – and applications – is to go “stateless.” The reasons for this are many, but in general by eliminating the mapping between a single client and a single app or service instance you eliminate the need for resources to manage state in the app (overhead) and improve the distributability (I can make up words if I want) of requests across a pool of instances. The latter occurs because sessions don’t need to hang out and consume resources that could be used to serve other requests. Distribution should, in theory, be more even and enable better pred...

Approved this February by the Internet Engineering Task Force (IETF), HTTP/2 is the first major update to HTTP since 1999, when HTTP/1.1 was standardized. Designed with performance in mind, one of the biggest goals of HTTP/2 implementation is to decrease latency while maintaining a high-level compatibility with HTTP/1.1. Though not all testing activities will be impacted by the new protocol, it's important for testers to be aware of any changes moving forward.

This week, I joined SOASTA as Senior Vice President of Performance Analytics. Given my background in cloud computing and distributed systems operations — you may have read my blogs on CNET or GigaOm — this may surprise you, but I want to explain why this is the perfect time to take on this opportunity with this team. In fact, that’s probably the best way to break this down. To explain why I’d leave the world of infrastructure and code for the world of data and analytics, let’s explore the timing, the opportunity, and the team that brought me to SOASTA.

You often hear the two titles of "DevOps" and "Immutable Infrastructure" used independently.
In his session at DevOps Summit, John Willis, Technical Evangelist for Docker, covered the union between the two topics and why this is important. He provided an overview of Immutable Infrastructure then showed how an Immutable Continuous Delivery pipeline can be applied as a best practice for "DevOps." He ended the session with some interesting case study examples.

Auto-scaling environments, micro-service architectures and globally-distributed teams are just three common examples of why organizations today need automation and interoperability more than ever. But is interoperability something we simply start doing, or does it require a reexamination of our processes? And can we really improve our processes without first making interoperability a requirement for how we choose our tools?

Cloud Migration Management (CMM) refers to the best practices for planning and managing migration of IT systems from a legacy platform to a Cloud Provider through a combination professional services consulting and software tools.
A Cloud migration project can be a relatively simple exercise, where applications are migrated ‘as is’, to gain benefits such as elastic capacity and utility pricing, but without making any changes to the application architecture, software development methods or business processes it is used for.

The Internet of Things. Cloud. Big Data. Real-Time Analytics. To those who do not quite understand what these phrases mean (and let’s be honest, that’s likely to be a large portion of the world), words like “IoT” and “Big Data” are just buzzwords. The truth is, the Internet of Things encompasses much more than jargon and predictions of connected devices. According to Parker Trewin, Senior Director of Content and Communications of Aria Systems, “IoT is big news because it ups the ante: Reach out and touch somebody is becoming reach out and touch everything.” In my previous blog, we talked about...

At DevOps Summit NY there’s been a whole lot of talk about not just DevOps, but containers, IoT, and microservices. Sessions focused not just on the cultural shift needed to grow at scale with a DevOps approach, but also made sure to include the network ”plumbing” needed to ensure success as applications decompose into the microservice architectures enabling rapid growth and support for the Internet of (Every)Things.

Our guest on the podcast this week is Adrian Cockcroft, Technology Fellow at Battery Ventures. We discuss what makes Docker and Netflix highly successful, especially through their use of well-designed IT architecture and DevOps.

Digital Transformation is the ultimate goal of cloud computing and related initiatives. The phrase is certainly not a precise one, and as subject to hand-waving and distortion as any high-falutin' terminology in the world of information technology.
Yet it is an excellent choice of words to describe what enterprise IT—and by extension, organizations in general—should be working to achieve.
Digital Transformation means:
handling all the data types being found and created in the organization
understanding that through mobility, data is being generated and analyzed on the edges of the e...

Puppet Labs has published their annual State of DevOps report and it is loaded with interesting information as always. Last year’s report brought home the point that DevOps was becoming widely accepted in the enterprise. This year’s report further validates that point and provides us with some interesting insights from surveying a wide variety of companies in different phases of their DevOps journey.

Microservices are hot. And for good reason. To compete in today’s fast-moving application economy, it makes sense to break large, monolithic applications down into discrete functional units. Such an approach makes it easier to update and add functionalities (text-messaging a customer, calculating sales tax for a specific geography, etc.) and get those updates / adds into production fast. In fact, some would argue that microservices are a prerequisite for true continuous delivery.
But is it too soon to talk about keeping microservices lifecycle costs under control?

Summer is finally here and it’s time for a DevOps summer vacation. From San Francisco to New York City, our top summer conferences list is going to continuously deliver you to the summer destinations of your dreams.
These DevOps parties are hitting all the hottest summer trends with Microservices, Agile, Continuous Delivery, DevSecOps, and even Continuous Testing. Move over Kanye. These are the top 5 Summer DevOps Conferences of 2015.

Microservices Journal focuses on the business and technology of the software architecture design pattern, in which complex applications are composed of small, independent processes communicating with each other using language-agnostic APIs.

Cloud computing budgets worldwide are reaching into the hundreds of billions of dollars, and no organization can survive long without some sort of cloud migration strategy. Each month brings new announcements, use cases, and success stories.